1

Machine Learning Petroleum Engineer Jobs in Riverside, CA

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $154K/yr

We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results ...

Lead AI Engineer

Irvine, CA

$110K - $144K/yr

Description The Lead AI Engineer will be responsible for defining and driving the AI strategy ... Design, develop, and deploy advanced AI models and algorithms, including machine learning, deep ...

Sr Engineer, AI Solutions

Irvine, CA · On-site

$130K - $168K/yr

The Senior Engineer, AI Solutions collaborates with cross-functional teams to design, develop, and ... Design and implement AI/Machine Learning (ML) solutions across domains such as computer vision and ...

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an ...

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an ...

Senior Software Engineer, MLOps

Irvine, CA · On-site

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an ...

Applied AI Engineer

Irvine, CA · On-site

$160K - $190K/yr

Train, fine-tune, validate, and optimize machine learning models for performance, scalability, and ... Collaborate with data engineers to collect, preprocess, and clean structured and unstructured data ...

Train, fine-tune, validate, and optimize machine learning models for performance, scalability, and ... Collaborate with data engineers to collect, preprocess, and clean structured and unstructured data ...

next page

Showing results 1-20

Machine Learning Petroleum Engineer information

See Riverside, CA salary details

$32.9K

$134.3K

$201.9K

How much do machine learning petroleum engineer jobs pay per year?

As of Jun 27, 2026, the average yearly pay for machine learning petroleum engineer in Riverside, CA is $134,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,900.00 and $161,700.00 per year, depending on experience, location, and employer.

Is ML a high paying job?

Machine Learning Petroleum Engineers typically earn high salaries due to their specialized skills in data analysis, modeling, and the oil and gas industry. Compensation varies based on experience, location, and certifications, but overall, it is considered a well-paying role within engineering fields.

How does a Machine Learning Petroleum Engineer typically collaborate with geoscientists and drilling teams to optimize oil and gas production?

A Machine Learning Petroleum Engineer works closely with geoscientists and drilling teams by integrating data-driven models into exploration and production workflows. They analyze geological, seismic, and operational data to develop predictive algorithms that identify optimal drilling locations, forecast reservoir performance, and improve recovery rates. Regular collaboration involves translating complex data insights into actionable recommendations that guide drilling strategies and inform real-time decisions, ensuring all teams are aligned to maximize efficiency and safety. This multidisciplinary approach fosters continuous learning and innovation across teams.

What engineers make $500,000?

Senior petroleum engineers, especially those with extensive experience, advanced technical skills, and leadership roles, can earn salaries of $500,000 or more annually. High compensation is often associated with working in major oil and gas companies, offshore environments, or in executive positions that require specialized expertise and certifications.

What is the difference between Machine Learning Petroleum Engineer vs Reservoir Engineer?

AspectMachine Learning Petroleum EngineerReservoir Engineer
Required CredentialsBachelor's/Master's in Petroleum Engineering, Data Science, or related fields; knowledge of machine learningBachelor's/Master's in Petroleum Engineering or Geosciences; strong understanding of reservoir simulation
Work EnvironmentData analysis, modeling, software development in oil & gas companiesReservoir modeling, field development planning in oil & gas operations
Industry UsageApplying machine learning to optimize extraction, predict reservoir behaviorEstimating reservoir properties, managing production strategies

The Machine Learning Petroleum Engineer focuses on integrating data science and machine learning techniques to optimize oil extraction processes, while the Reservoir Engineer specializes in modeling and managing subsurface reservoirs to maximize recovery. Both roles are vital in the oil & gas industry but differ in their core skills and daily tasks.

What is a Machine Learning Petroleum Engineer?

A Machine Learning Petroleum Engineer is a specialist who combines expertise in petroleum engineering with machine learning and data science techniques. They use advanced algorithms and data analytics to optimize oil and gas exploration, drilling, production, and reservoir management. Their work helps improve decision-making, reduce operational costs, and increase efficiency by analyzing large datasets from various sources such as sensors, seismic data, and production logs. These professionals often work closely with geoscientists, data engineers, and other stakeholders in the energy sector.

What engineers make $300,000 a year?

Senior machine learning petroleum engineers with extensive experience, advanced skills in data analysis and modeling, and often working in leadership roles or specialized environments can earn $300,000 or more annually. High compensation typically involves working for major energy companies, possessing relevant certifications, and contributing to complex projects that impact production and exploration strategies.

What are the key skills and qualifications needed to thrive as a Machine Learning Petroleum Engineer, and why are they important?

To thrive as a Machine Learning Petroleum Engineer, you need a strong background in petroleum engineering, programming (such as Python or R), and applied machine learning, usually supported by a relevant engineering degree. Familiarity with data analysis platforms, machine learning frameworks (like TensorFlow or Scikit-learn), and petroleum industry software (such as Petrel or Eclipse) is essential. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for integrating technical insights with business goals. These competencies enable the effective application of data-driven solutions to optimize exploration, production, and operational efficiency in the energy sector.

Will AI take over petroleum engineering?

AI can assist petroleum engineers by improving data analysis, reservoir modeling, and automation of routine tasks. However, the role of a petroleum engineer involves complex decision-making, field supervision, and problem-solving that require human expertise, making complete automation unlikely in the near future.
What are popular job titles related to Machine Learning Petroleum Engineer jobs in Riverside, CA? For Machine Learning Petroleum Engineer jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Petroleum Engineer jobs in Riverside, CA look for? The top searched job categories for Machine Learning Petroleum Engineer jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Machine Learning Petroleum Engineer jobs? Cities near Riverside, CA with the most Machine Learning Petroleum Engineer job openings:
Principal Machine Learning Engineer

Principal Machine Learning Engineer

Cisco

Irvine, CA • On-site

$291K - $369K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 1 hour ago


Cisco Systems rating

8.0

Company rating: 8.0 out of 10

Based on 40 frontline employees who took The Breakroom Quiz

47th of 139 rated electronics manufacturers


Job description

The application window is expected to close on:

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

Meet the Team

Splunk, a Cisco company, is building a safer, more resilient digital world with an endtoend, fullstack platform designed for hybrid, multicloud environments. Join theAI Modelsteam at Splunk, where we advance the state of AI for highvolume, realtime, multimodal machinegenerated data - including logs, time series, traces, and events. We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco's global engineering capabilities. Our work spans networking, security, observability, and customer experience - designing and deploying foundation models that enhance reliability, strengthen security, preventdowntime, and deliver predictive insights across Splunk Observability, Security, and Platform at enterprise scale. You'll be part of a culture that values technical excellence, impactdriven innovation, and crossfunctional collaboration - all within a flexible, growthoriented environment.

Your Impact

  • Set and Drive Vision:Define and champion the strategic vision for AI and foundation models across Splunk and Cisco platforms, shaping the research and technology roadmap to anticipate and address industrydefining challenges.

  • Architect and Lead Breakthroughs: Lead the endtoend lifecycle of research, design, and deployment for largescale foundation models targeting machinegenerated data, with deep focus on logs and complementary modalities (time series, traces, events).

  • Influence at Scale: Partner with executive leadership, engineering, product, and data science teams to ensure AI solutions align with broader organizational objectives, product strategies, and customer needs.

  • Mentorship and Thought Leadership: Cultivate organizational excellence by mentoring senior technical talent, fostering research communities, and driving best practices in AI across global teams.

  • Foster Innovation: Embed cuttingedge research and technological advances into products, driving sustained competitive advantage and transformation at enterprise scale.

Minimum Qualifications:

  • PhD in Computer Science, or related quantitative field, plus7+ years of industry research experience.

  • Proven track record in at least one of the following areas: large language modeling for both structure and unstructured data, deep learningbased time series modeling, advanced anomaly detection, and multi-modality modeling.

  • Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)

  • Experience translating research ideas into production systems.

Preferred Qualifications:

  • Deep NLP & DomainAdapted LLMs: Background in building and adapting largescale language models (e.g., T5, BERT, LLaMA, GPTs) for specialized domains including structured/unstructured logs, text, and event sequences.

  • Log Analytics Expertise - Indepth knowledge of structured/unstructured system logs, event sequence analysis, anomaly detection, and root cause identification.

  • Advanced Anomaly Detection - Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for highvolume, realtime logs data.

  • MultiModal AI Modeling - Strong track record fusing logs, time series, traces, tabular data, and graphs for foundation models tackling complex operational insights.

  • LargeScale Training & Optimization - Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.

  • MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.

  • Strong Research Track Record - Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to stateoftheart methods and realworld applications.

Why Cisco?

At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Message to applicants applying to work in the U.S. and/or Canada:The starting salary range posted for this position is $291,500.00 to $369,100.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco's policies:

  • 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees

  • 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco

  • Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees

  • Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)

  • 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours ofunused sick timecarried forwardfrom one calendar yearto the next

  • Additional paid time away may be requested to deal with critical or emergency issues for family members

  • Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

  • .75% of incentive target for each 1% of revenue attainment up to 50% of quota;

  • 1.5% of incentive target for each 1% of attainment between 50% and 75%;

  • 1% of incentive target for each 1% of attainment between 75% and 100%; and

  • Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area:

$291,500.00 - $424,400.00

Non-Metro New York state & Washington state:

$259,400.00 - $377,600.00

* For quota-based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.

** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.


What Cisco Systems employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Cisco Systems logo

About Cisco Systems

Sourced by ZipRecruiter

Cisco Systems, a global tech titan based in San Jose, CA, US, operates in the information technology and services industry. Founded in 1984, the company was derived from a project between two computer scientists from Stanford University. They aimed to connect different networks of computer systems at the university, resulting in the first multi-protocol router, and subsequently, the birth of Cisco. As an industry-leading manufacturer of networking hardware and telecommunications equipment, Cisco's product and services range includes routers, switches, firewall devices, and telecommunication technology. The company's mission, "to shape the future of the Internet by creating unprecedented value and opportunity for our customers, employees, investors, and ecosystem partners," is a testament to its pursuit of technology-forward innovation and customer satisfaction.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1984

Social media